Obesity is a global epidemic that is causally associated with a range of diseases, including type 2 diabetes and cardiovascular disease, at the population-level. However, there is marked heterogeneity in obesity-related outcomes among individuals. This might reflect genotype-dependent responses to adiposity. Given that adiposity, measured by BMI, is associated with widespread changes in gene expression and regulatory variants mediate the majority of known complex trait loci, we sought to identify gene-by-BMI (G × BMI) interactions on the regulation of gene expression in a multi-tissue RNA-sequencing (RNA-seq) dataset from the TwinsUK cohort (n = 856). At a false discovery rate of 5%, we identified 16 cis G × BMI interactions (top cis interaction: CHURC1, rs7143432, p = 2.0 × 10−12) and one variant regulating 53 genes in trans (top trans interaction: ZNF423, rs3851570, p = 8.2 × 10−13), all in adipose tissue. The interactions were adipose-specific and enriched for variants overlapping adipocyte enhancers, and regulated genes were enriched for metabolic and inflammatory processes. We replicated a subset of the interactions in an independent adipose RNA-seq dataset (deCODE genetics, n = 754). We also confirmed the interactions with an alternate measure of obesity, dual-energy X-ray absorptiometry (DXA)-derived visceral-fat-volume measurements, in a subset of TwinsUK individuals (n = 682). The identified G × BMI regulatory effects demonstrate the dynamic nature of gene regulation and reveal a functional mechanism underlying the heterogeneous response to obesity. Additionally, we have provided a web browser allowing interactive exploration of the dataset, including of association between expression, BMI, and G × BMI regulatory effects in four tissues.